Conceptual and quantitative categorization of wave-induced flooding impacts for pedestrians and assets in urban beaches

Beaches combined with sloping structures are frequently the first element of defense to protect urban areas from the impact of extreme coastal flooding events. However, these structures are rarely designed for null wave overtopping discharges, accepting that waves can pass above the crest and threat exposed elements in hinterland areas, such as pedestrians, urban elements and buildings, and vehicles. To reduce risks, Early Warning Systems (EWSs) can be used to anticipate and minimize the impacts of flooding episodes on those elements. A key aspect of these systems is the definition of non-admissible discharge levels that trigger significant impacts. However, large discrepancies in defining these discharge levels and the associated impacts are found among the existing methods to assess floodings. Due to the lack of standardization, a new conceptual and quantitative four-level (from no-impact to high-impact) categorization of flood warnings (EW-Coast) is proposed. EW-Coast integrates and unifies previous methods and builds on them by incorporating field-based information. Thus, the new categorization successfully predicted the impact level on 70%, 82%, and 85% of the overtopping episodes affecting pedestrians, urban elements and buildings, and vehicles, respectively. This demonstrates its suitability to support EWSs in areas vulnerable to wave-induced flooding.


Results
Conceptual impact level classification. A new classification of wave overtopping impacts (and the associated discharge limits) on three coastal elements with high relevance in urban beach areas, namely pedestrians, urban components and buildings, and vehicles, hereafter called EW-Coast, was created. The unified warning level classification involves four warning levels based on the severity of the damage, from no impact (green color) to high impact (red color), with two intermediate levels (yellow and orange), as displayed in Table 2.
For pedestrians, no impact means that wave overtopping does not induce injuries or threats, even for the most vulnerable population, e.g., the elderly and children. Low impact implies that only the most vulnerable population can suffer minor injuries that do not threaten their lives. Moderate impact indicates that most people can be exposed to a fall due to friction instability (slipping) or moment (toppling) or being hit by debris, and only an alerted and active person can avoid the damage. High impact implies unsafe to everyone. www.nature.com/scientificreports/ Regarding the urban components and buildings, no impact represents that the urban components, namely fittings, posts and non-structural elements, such as windows and doors, can resist the flow impacts without any damage. For low impact, those elements are marginally damaged, while for moderate impact, they are severely damaged. High impact implies structural damage or building collapse.
For vehicles at low speed, no impact means that any vehicle can be driven safely. Low impact denotes that the overtopping flow can destabilize some very light vehicles, such as bicycles and light motorbikes, and/or can scare unaware drivers, not expecting to get wet, interfering briefly with their capacity to drive. The moderate impact means that small passenger cars, whose mass is equal to or lower than 1000 kg 15 , might become unstable and/ or drivers may temporarily lose control of their vehicle if water hits the front window. The high impact implies that any conventional passenger car (two-wheel drive) will experience slipping and it is very dangerous to drive. Several examples from the study sites (CC and PdF) illustrating critical situations within the considered warning levels ( Table 2) are depicted in Fig. 1.
The categories of the critical levels proposed by the existing assessment methods were reclassified (see Table 3) to agree with the unified definition shown in Table 2. The methods included here were Coastal Engineering Manual 13 (hereafter CEM), EurOtop 2018 7 (hereafter EurOtop), HIDRALERTA 14,16 , and FLOODsite 17 . It is important to state that some works, e.g., EurOtop only defines two levels of impact, tolerable and not tolerable, and therefore this method can be only considered in two warning categories as shown in Table 3. For this case, the impact levels of EurOtop were categorized as green and orange for pedestrians, green and red for urban components and buildings, and green and orange for vehicles (Table 3). For CEM, the four critical levels for pedestrians were adapted to agree with the classification presented in Table 2. Also, the orange level was omitted  www.nature.com/scientificreports/ for urban components and buildings because only three impact levels are described in this manual for these assets. Moreover, CEM establishes specific limits for vehicles that are driven at low speed (here at the crest or behind the seawall depending on the study site, Table 1). Only two levels, green and orange, were considered for this asset (Table 3). For HIDRALERTA, four categories of warnings were used for pedestrians, urban components and buildings, and vehicles. FLOODsite considers four impact levels for pedestrians, which can be fitted in the warning gradation proposed in Table 2, while for the remaining elements, the low impact level was not considered (Table 3).
Existing methods assessment. The Tables S1 and S5). The obtained impact levels were then compared against observed impacts for analysis and validation. From the comparison between the predicted and observed impacts, it was found that: (1) Regarding the ability to predict impacts on pedestrians, FLOODsite displayed the best skills, as 73% of the overtopping episodes were well prognosticated against 42% for EurOtop, with the lowest skills (Fig. 2). Moreover, EurOtop's predictions underestimated the observed impacts in 58% of the cases. HIDRALERTA and CEM exhibited similar ability to anticipate the impact levels (69% and 65% of the episodes were well predicted, respectively), with the former method underpredicting 15.5% of the cases against 23% by the latter method (Fig. 2). (2) Regarding urban components and buildings, FLOODsite was also the best of the existing methods, with 65% of the cases well predicted, against the worst estimates from CEM, which only agreed with the observations in 39% of the cases and over- www.nature.com/scientificreports/ estimated the observed impacts in 57% of the episodes (39.5% overestimations in more than one warning level) (Fig. 2). EurOtop's estimations agreed well with the observations in 56% of the cases and HIDRALERTA's in 52%, with both methods overpredicting the observed impacts on 26% and 39% of the cases respectively ( Fig. 2).
(3) Regarding vehicles, FLOODsite predicted correctly 70% of the cases, EurOtop and HIDRALERTA 65%, and CEM 50%. When analyzing the general performance of the existing methods (the three exposed elements together), discrepancies between predicted and observed impacts in more than one level (under and overprediction) accounted for 12% for FLOODsite, 22% for EurOtop, 17% for HIDRALERTA, and 25% for CEM (Fig. 2).
Unified impact level threshold definition. The assessment displayed in Fig. 2 highlighted that there was no single method capable of providing robust and reliable estimations for all considered levels and coastal elements. The new proposed unified categorization, besides being conceptual (Table 2), must also be translated into thresholds that distinguish different warning levels for each type of exposed element. The newly proposed association between wave overtopping discharges and each warning level (EW-Coast method) for the considered exposed elements is presented in Table 4. The critical wave overtopping discharge limits were defined based on the assessment of the existing methods and the impact observations. The limits vary depending on the resistance and vulnerability of the elements. For instance, for pedestrians, low and high impact warnings require discharges of at least 0.03 and 1 l/s per m respectively, while for urban components and buildings, the same warning levels require discharges of at least 1 and 20 l/s per m respectively.
Unified impact level threshold assessment. The same mean wave overtopping discharge computations used in the previous assessment were considered to estimate the warning levels for the pedestrians and coastal assets based on the limits shown in Table 4. Based upon Fig. 3, the comparison between the predicted and observed impacts revealed that: (1) Regarding pedestrians, EW-Coast, correctly predicted 69.5% of the overtop- www.nature.com/scientificreports/ ping episodes, while the majority of the situations (92.5%) agreed with the observed impact or were within one level of difference (overestimation or underestimation) with respect to the observations. (2) Regarding urban components and buildings, EW-Coast identified 82% of the cases (Fig. 3), largely overcoming the performance of existing methods, as shown in Fig. 2. (3) Regarding vehicles, 85% of the cases were well-predicted by EW-Coast overcoming all the existing methods. For this asset, 5% of the cases underestimated the observations in one level and 10% in two levels. Moreover, for the three exposed elements together, only 9% of the predicted cases presented a difference with the observations of more than one warning level.

Discussion
Coastal structures are rarely designed for zero overtopping during extreme storms 10 and therefore managers must be prepared to implement specific risk-reduction measures when wave overtopping exceeds acceptable limits that jeopardize the functional safety of seawalls, promenades, or boulevards 10 . However, as demonstrated, the existing methods do not provide a standard description of potential impacts on pedestrians and coastal assets related to urban beaches and differ in the predicted warning level for the same event and exposed element. That is most probably related to the large variability among those methods regarding the discharge limits that induce critical situations and their severity. Therefore, varying predictive skill was found among the existing methods, with most of them presenting large percentages of underprediction or overprediction of the observed impacts (Fig. 2). It was found that overall, the existing methods failed in correctly predicting the warning level in between 27 and 61% of the cases. Moreover, the average percentage of failure considering together the three types of exposed elements was 48% for CEM, 45% for EurOtop, 38% for HIDRALERTA and 30% for FLOODsite. A systematic underprediction might not anticipate impacts and a frequent overprediction can release false alarms that will discredit the predictions. Under the demand for a clear and unified flood level characterization with verified limits that can be applied to urban beaches, a classification of impact levels for pedestrians, urban components and buildings, and vehicles that integrates all existing methods is presented. The assessment of the new proposed limits revealed that they overcame the existing methods in predicting the warning levels with the erroneous predictions being reduced to an average (three exposed elements) of 21%, indicating an improved prediction between 27 and 9% with respect to the methods with the lowest and highest skills. Furthermore, when comparing against the existing method with the highest skills (FLOODsite), EW-Coast reduced the erroneous predictions by 17% and 15% in urban elements and buildings, and vehicles respectively while both methods obtained a similar percentage of failures for pedestrians (~ 30%).
The limits proposed here for pedestrians are within the same order of magnitude as those for HIDRALERTA. These limits are also in line with others used in early warning systems namely Triton in England 18 , which establishes the lowest level of warning when mean overtopping exceeds 0.1 l/s per m. This value was inspired by the perceived overtopping threshold documented by Belloti et al. 19 on a field survey. For vehicles, the new limits are in line with those proposed in EurOtop (when the incident significant wave height, H m0 , at the toe of the Table 4. Unified mean discharge limits (l/s per m) of EW-Coast to split between different warning levels. www.nature.com/scientificreports/ structure exceeds 3 m). Conversely, the limits proposed for urban components and buildings are higher than the existing methods and this promoted a better agreement with the observations, while the other methods highly overestimated the impacts. Therefore, the unified mean discharge limits proposed in this study, were inspired by a review of the pre-existent knowledge generated by well-known methodologies (Coastal Engineering 13 , EurOtop 2018 7 , HIDRALERTA 14 and FLOODsite 17 ) and altered based on field observations enabling the creation of a more robust classification that better characterizes the wave-induced impacts.
In the present study, for each condition, wave overtopping was simulated five times with the process-based model XBeach 20 (non-hydrostatic mode) by using nominally identical JONSWAP wave spectra parameters, but randomly varying the initial seed value. Instead of the minimum or the average values, the maximum value of mean discharge among the five simulations was selected to characterize the hazard as it was observed that, in general, this value resulted in the best agreement with the observations for the assessment methods investigated. The overtopping estimations of physical experiments and numerical models simulating the propagation and decay of individual waves (e.g. XBeach 20 and SWASH 21 ) are subject to uncertainties due to the inherent randomness of the overtopping process. In fact, McCabe et al. 22 declared that wave overtopping was very sensitive to changes in the initial seed and the overall overtopping rates can differ by up to a factor of two for nominally identical wave conditions. Williams et al. 23 noticed that variability due to the seeding was larger for low overtopping conditions. Furthermore, the physical phenomenon of overtopping is affected by the specific sequence of waves that arrives at the shore 24 . However, as the phase distribution cannot be predicted, this adds uncertainty to any method of obtaining overtopping predictions 23,25 . There are other less complex methods to simulate wave overtopping, including empirical formulas 7,26 that neglect that uncertainty, unless they are used within a probabilistic approach. However, they include some simplifications (for instance the beach profile) and the infragravity energy is not considered, while the effects of the stochastic uncertainty of the random phasing can be very relevant when predicting overtopping discharges 25 .
Collecting overtopping measurements in the field is very challenging 27 , and therefore, information to conduct a proper validation against quantitative data of any of the different methods to estimate overtopping in real conditions is very scarce 25 . Therefore, the comparison and validation of overtopping critical limits against observed data have rarely been investigated. Here, the high level of agreement with the impact observations and the ability of the predictive method to respond to varying storm conditions (from no-overtopping to remarkably high discharge values) guarantee a good accuracy that relates correctly the impact with the existing physical processes. Moreover, numerical models based on the non-linear shallow water equations with a pressure correction term, such as XBeach 20 (non-hydrostatic mode) and SWASH 21 are rapidly increasing their utilization for similar analyses confirming their suitability for wave overtopping studies 25 . Importantly, XBeach has shown good accuracy skills in simulating wave runup and mean overtopping discharges in dikes fronted by a shallow foreshore 28 with similar characteristics to the cross-shore profiles assessed here. It is important to remark that the variability of the wave overtopping estimations provided by different methods (numerical models, empirical formulas and neuronal networks) can be very important 29,30 as well as the subsequent impact predictions. However, this short of uncertainty depends on the methods used for the hazard computations and not on the proposed thresholds categorizing the warning levels.
In the present study, the feedback mechanisms between beach morphology and wave runup are not simulated and this can represent a major limitation. While feedback mechanisms are not expected in the upper part of the studied areas (man-made rigid structures), these can be relevant at the fronting beach profile. Previous studies [31][32][33] have demonstrated that the morphological evolution of the sandy bottom highly affects the maximum wave runup, the time-integrated total wave overtopping volume and the timing of peak wave overtopping. While the effect of the morphological evolution can affect wave overtopping, most available methods to simulate wave-induced floodings, such as empirical formulas 26,34 , neuronal network tools 35 , and specific numerical models 20,21,36,37 , neglect the morphodynamic response. However, if there are strong morphodynamic feedbacks between beach morphology and runup incursions, then these methods are no longer valid and other alternatives might be required (e.g. XBeach 20 surfbeat or IH2VOF-SED 38 ). Another source of uncertainty is the lack of pre-storm beach topography measurements to be implemented in the numerical model for each storm. Instead, representative pre-storm conditions (from topographical surveys) were implemented in the numerical model. The existence of an unusually large berm width or beach scarp can affect the runup propagation, especially for low overtopping conditions 39 .
In areas with an energetic wave climate, watching violent waves breaking and overtopping can promote considerable public interest 40 increasing the possibility of injuries to people and damage to vehicles, at the same time that buildings or urban elements can be affected. Therefore, authorities should adopt risk-reduction measures to minimize damage or even fatalities associated with overtopping hazards. If the new verified and unified impact characterization is implemented in operational and warning systems, decision-makers will be informed in advance about potential flooding-induced damages, being able to activate risk-reduction measures that safeguard pedestrians and assets on coastal defenses, promenades, or boulevards on urban beaches. It is important to remark that these thresholds are only applicable in areas with similar settings to those evaluated here (i.e., excluding high vertical structures where impulsive, violent, and sudden overtopping may occur, with falling or high-velocity jets). This integrated classification will also support the implementation of alert systems endorsing the fulfillment of the priorities defined in the Sendai Framework for Disaster Risk Reduction 2015-2030 and the United Nations Sustainable Development Goals 41 (1, 3, 8, 11, 13 and 14).  10 . In the older version, a limit of 0.1 l/s per m was established for pedestrians aware of the hazards with a clear view of the sea. This limit was derived mainly from observations 11,44,48,49 and additional measurements of the CLASH project 40,50 . A further precautionary limit of 0.03 l/s per m was also suggested for unusual conditions where pedestrians have no clear view of incoming waves; may be easily upset or frightened as they are not dressed to get wet; may be on a narrow walkway or close proximity to a drip or fall hazard (not all of these conditions are required simultaneously). In the newer version, the authors defined three limits for overtopping for pedestrians at the crest of a structure with a clear view of the sea and considering that the expected overtopping is neither sudden nor violent based on estimations and measurements of overtopping at two breakwaters (Oostende and Ostia) and physical experiments 7 . Those limits are 0.3, 1, and 10-20 l/s per m for incoming H m0 , at the toe of the structure of 3, 2 and 1 m, respectively, as it is considered that even for the same mean discharges, higher waves promote higher maximum volumes. In the present study, at CC the toe of the structure was considered at the intersection between the foreshore and the seawall, while at PdF as the structure is buried the toe of the structure was considered as the transition between the low tide terrace and the foreshore. For vehicles, in EurOtop 2018 7 , the tolerable limits no longer discriminate between low and high speeds (as was specified in EurOtop 2007 10 ) and three tolerable limits are presented: 5, 10-20 and 75 l/s per m, depending on the H m0 value at the toe of the structure. It is assumed that these vehicles are driven in an area with access to people and thus, the speed is not high. The tolerable limit proposed in EurOtop 2018 7 for structural components of buildings is 1 l/s per m and it is based on estimations of overtopping at the Belgium coast. Importantly, impact gradation is not considered for any of the elements introduced. HIDRALERTA 14,16 establishes four impact categories, no impact, minor, serious and extreme, and the associated mean wave overtopping limits for different coastal elements. The limits that the authors provide to categorize the impacts are based on recommendations from EurOtop 2007 10 and observations reported by coastal and port authorities in a limited number of coastal areas and harbors in Portugal. While HIDRALERTA was initially devoted to port activities, some actors, such as pedestrians, vehicles and buildings, can be also present on urban beaches and therefore, they were also considered on the current study. For pedestrians, HIDRALERTA separates between aware and unaware people. It is important to declare that this study only gathered damage data related to fluvial flooding, and coastal environments were not included. Therefore, the considered limits are an adaptation to overtopping induced damages. As suggested by the FLOODsite authors' , when comprehensive information about the exposed elements is not available, the medium vulnerability category was selected. The values of maximum depth-velocity product to characterize the considered impact levels for pedestrians, buildings and vehicles were adapted from their Fig. 2(6). The model offers four different levels of hazards: low, medium, high and extreme. However, for buildings and vehicles, only three levels were considered here. For pedestrians and vehicles, depth-velocity reaching 0.25 m 3 /s per m results in critical situations. When the depth-velocity is equal to or higher than 1.1 m 3 /s per m represents extreme damage for pedestrians and possible structural damage in buildings. All this information is summarized in Supplementary Tables S2 and S3, which were adapted from the original methods.

Study cases.
The new warning level description with the associated unified limits was developed and tested at two coastal areas in Portugal with contrasting wave regimes. Costa da Caparica (CC) is a mesotidal (dominated by semidiurnal constituents), sandy, urban beach located in the municipality of Almada, on the west coast of Portugal, a few kilometers south of the outer Tagus estuary 51 . This urban area is under intensive human pressure with several touristic and economic activities located on the seawall crest 51 . The coastline was severely modified with hard defense structures such as sloping rock armour seawalls (Fig. 4), which avoid its retreat, and a groin field. The groin field creates six sandy cells with an alongshore length that varies between 250 and 400 m. Two of these cells were evaluated here, CC1 (Santo António beach) and CC2 (Tarquineo-Paraiso beach) (Fig. 4). Cell CC1 is characterized by a 145 m beach width (from the seawall toe to the mean sea level, MSL, shoreline) at its central part (average conditions) and the seawall crest is 6.36 m above MSL. Cell CC2 has a wider beach, around 170 m (from the seawall toe to the MSL shoreline) for average conditions, and the elevation of the seawall www.nature.com/scientificreports/ crest is 6.04 m above MSL. In contrast to CC1, at this beach cell, the seawall crest has the same elevation as the surrounding landscape and thus, there is no shift in elevation in the area behind the crest (Fig. 4). Praia de Faro (PdF) is located on the Ancão Peninsula, the westernmost sector of the Ria Formosa barrier island system, on the southern coast of Portugal 52 . This narrow sand peninsula separates the Atlantic Ocean and a coastal lagoon and it is subject to a semidiurnal and mesotidal regime 52 . The section considered in this study is under intense urban development where the natural defense, namely the dune, was completely removed (Fig. 4) and the oceanfront is stabilized with a buried rip-rap seawall 52 , and a partially buried short wall (less than half a meter). These structures protect a 3 m-wide walking wooden path that gives access to the urbanized area with a large parking lot and several restaurants and cafes (Fig. 4). The beachfront promenade, accessible to pedestrians is 5.2 m above MSL, and the beach width is approximately 40 m, from the wall limiting the bathing area to the MSL shoreline.

Storms.
In order to assess the accuracy of the methods in predicting storm impacts for pedestrians and assets, several storms with different levels of intensity were selected as shown in Supplementary Table S1. Insitu observations and videos from YouTube were collected (see some examples in Fig. 1) during these storms and then, based on the authors' judgment, the induced impact levels were classified according to Table 2. On the two beach cells from CC, storm Hercules 2014, which brought severe damage along the entire Portuguese coast, storm Emma 2018, and another storm in 2017, hereafter referred to as Feb2017, were used to compare the predictions of the methods and the observations. In PdF, five storms were selected: storm Hercules 2014, storm Emma 2018, storm Elsa 2019, storm Barbara 2020, and storm Lola 2021, where for the first and the last storms more than one sea-state were included in the analysis (Supplementary Tables S1 and S4). The oceanic and atmospheric conditions during these storms used as input information for the wave overtopping computations were extracted from official systems (ERA-5 hindcast and Puertos del Estado), XTIDE (www. flate rco. com/ xtide) and nearby observations (tidal gauge and wave buoy) (see modeling description below). The wave and sea level conditions during these storms in front of both sites are shown in Supplementary Table S1.
Wave overtopping modeling. To model wave overtopping at CC, a numerical framework was used consisting of SWAN 53 + XBeach 20 . The SWAN model used a nested approach with two structure grids to simulate wave processes from deep water to the offshore boundary of the XBeach model (~ 22 m depth). The outer grid wave model had a resolution of 500 m (both in the cross-shore and along-shore directions) and it was forced along the domain boundaries with wave data from ERA-5 54 . Wind-transferred energy processes were also considered in the wave modeling by including temporally and spatially variable wind speed and direction information provided by ECMWF. The inner grid wave model was forced along the domain boundaries with wave information provided by the outer grid and it had a resolution of 100 m in both directions. The sea-bottom elevation data was extracted from two sources 55,56 . The default values of the model parameters were used. Then, two one-dimensional non-hydrostatic XBeach models (CC1 and CC2) were used to simulate nearshore processes of individual waves, short and long wave motions, run-up incursions, vertical exchange of ground and surface water, wave overtopping and flood propagation. However, these two models did not include geomorphological processes. The flow boundary conditions were set to nonh_1d in the front and abs_1d in the back and Neumann conditions were selected for the lateral boundaries. The CFL was set to 0.55. A two-layer scheme in the vertical with the layer distribution set to the default value (0.33) was applied to better simulate the dispersion relation and shoaling of waves in intermediate depths 57 . The parameter maxbrsteep that governs the maximum wave steepness criterium was set to 0.4. A constant manning coefficient of 0.02 was chosen to represent the bottom www.nature.com/scientificreports/ roughness. The grid resolution varied between 4 m (offshore) and less than 0.5 m in the nearshore and emerging areas. The nearshore and beach face elevations were extracted from surveys performed by the COSMO program (https:// cosmo. apamb iente. pt/) and they were considered to be representative of average conditions. The elevation of the seawall and the urbanized area were extracted from a survey conducted by the authors. These simulations used as input oceanic conditions the water level measurements from the tidal gauge at Cascais and the wave information obtained from the inner grid wave model. After a warm-up period, XBeach simulated 600 waves that multiplied by their mean period resulted in the time used to average the instantaneous wave overtopping discharges. Discharge values were extracted at the interest locations (the seaward and landward edge of the seawall crest and behind the promenade, as displayed in Table 1 and Supplementary Table S2) every half second, for both CC1 and CC2. To account for the stochastic effects of the wave overtopping process, the simulations were repeated five times with identical static water levels and wave parameters, but randomly varying the seed number used to generate the free surface elevation and velocity time series at the seaward boundary. The mean discharge used to assess the impact levels corresponded to the maximum among the five simulations. The modeling approach used in PdF involved the same numerical models. The SWAN model consisted of one structured grid that covered the entire southern Portuguese coast with an approximated resolution of 350 m and 600 m in the cross-shore and alongshore directions, respectively. The sea-bottom elevation was extracted from the open dataset MIRONE 58 . This model was forced with wave information provided by buoy measurements or numerical modeling from Puertos del Estado (https:// www. puert os. es/ en-us/ ocean ografi a/ Pages/ portus. aspx) imposed along the offshore model boundary that laid approximately at the 100 m bathymetric contour line. Using model default values, the wave conditions were propagated until 20 m depth, approximately, where the XBeach offshore boundary was located. Besides the wave conditions propagated to the model boundary, surge and tide levels from Huelva tidal gage and XTIDE respectively were used as input conditions for XBeach. Model parameters used in this model for PdF were similar to the parametrization used in CC and only maxbrsteep had a different value (0.5 instead of 0.4) to account for the particularities of this site. The grid resolution varied between 2 m (offshore) and 0.5 m (nearshore and emerging areas) and the sea-bottom and inland elevation was interpolated from several sources: a UAV survey conducted by the COSMO program that covered the emerged beach and the structure; a bathymetry survey performed by the COSMO program that measured the region from MSL until − 13.5 m MSL; and a regional bathymetry extracted from MIRONE 58 that was used to obtain information below − 13.5 m MSL.